Application of the NIA-AA Research Framework: Towards a Biological Definition of Alzheimer’s Disease using Cerebrospinal Fluid Biomarkers in the AIBL Study
S. Burnham, Preciosa M. Coloma, Qiao-Xin Li, Steven J. Collins, G. Savage, Simon M. Laws, Simon M. Laws, J. Doecke, P. Maruff, R. Martins, R. Martins, D. Ames, Christopher Rowe, Colin L. Masters, V. Villemagne
{"title":"Application of the NIA-AA Research Framework: Towards a Biological Definition of Alzheimer’s Disease using Cerebrospinal Fluid Biomarkers in the AIBL Study","authors":"S. Burnham, Preciosa M. Coloma, Qiao-Xin Li, Steven J. Collins, G. Savage, Simon M. Laws, Simon M. Laws, J. Doecke, P. Maruff, R. Martins, R. Martins, D. Ames, Christopher Rowe, Colin L. Masters, V. Villemagne","doi":"10.14283/jpad.2019.25","DOIUrl":null,"url":null,"abstract":"BackgroundThe National Institute on Aging and Alzheimer’s Association (NIA-AA) have proposed a new Research Framework: Towards a biological definition of Alzheimer’s disease, which uses a three-biomarker construct: Aß-amyloid, tau and neurodegeneration AT(N), to generate a biomarker based definition of Alzheimer’s disease.ObjectivesTo stratify AIBL participants using the new NIA-AA Research Framework using cerebrospinal fluid (CSF) biomarkers. To evaluate the clinical and cognitive profiles of the different groups resultant from the AT(N) stratification. To compare the findings to those that result from stratification using two-biomarker construct criteria (AT and/or A(N)).DesignIndividuals were classified as being positive or negative for each of the A, T, and (N) categories and then assigned to the appropriate AT(N) combinatorial group: A−T−(N)−; A+T-(N)−; A+T+(N)−; A+T−(N)+; A+T+(N)+; A−T+(N)−; A−T−(N)+; A−T+(N)+. In line with the NIA-AA research framework, these eight AT(N) groups were then collapsed into four main groups of interest (normal AD biomarkers, AD pathologic change, AD and non-AD pathologic change) and the respective clinical and cognitive trajectories over 4.5 years for each group were assessed. In two sensitivity analyses the methods were replicated after assigning individuals to four groups based on being positive or negative for AT biomarkers as well as A(N) biomarkers.SettingTwo study centers in Melbourne (Victoria) and Perth (Western Australia), Australia recruited MCI individuals and individuals with AD from primary care physicians or tertiary memory disorder clinics. Cognitively healthy, elderly NCs were recruited through advertisement or via spouses of participants in the study.ParticipantsOne-hundred and forty NC, 33 MCI participants, and 27 participants with AD from the AIBL study who had undergone CSF evaluation using Elecsys® assays.Intervention (if any)Not applicable.MeasurementsThree CSF biomarkers, namely amyloid β1–42, phosphorylated tau181, and total tau, were measured to provide the AT(N) classifications. Clinical and cognitive trajectories were evaluated using the AIBL Preclinical Alzheimer Cognitive Composite (AIBL-PACC), a verbal episodic memory composite, an executive function composite, California Verbal Learning Test–Second Edition; Long-Delay Free Recall, Mini-Mental State Examination, and Clinical Dementia Rating Sum of Boxes scores.ResultsThirty-eight percent of the elderly NCs had no evidence of abnormal AD biomarkers, whereas 33% had biomarker levels consistent with AD or AD pathologic change, and 29% had evidence of non-AD biomarker change. Among NC participants, those with biomarker evidence of AD pathology tended to perform worse on cognitive outcome assessments than other biomarker groups. Approximately three in four participants with MCI or AD had biomarker levels consistent with the research framework’s definition of AD or AD pathologic change. For MCI participants, a decrease in AIBL-PACC scores was observed with increasing abnormal biomarkers; and increased abnormal biomarkers were also associated with increased rates of decline across some cognitive measures.ConclusionsIncreasing biomarker abnormality appears to be associated with worse cognitive trajectories. The implementation of biomarker classifications could help better characterize prognosis in clinical practice and identify those at-risk individuals more likely to clinically progress, for their inclusion in future therapeutic trials.","PeriodicalId":48606,"journal":{"name":"Jpad-Journal of Prevention of Alzheimers Disease","volume":"1 1","pages":"1-8"},"PeriodicalIF":8.5000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14283/jpad.2019.25","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jpad-Journal of Prevention of Alzheimers Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.14283/jpad.2019.25","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 26
Abstract
BackgroundThe National Institute on Aging and Alzheimer’s Association (NIA-AA) have proposed a new Research Framework: Towards a biological definition of Alzheimer’s disease, which uses a three-biomarker construct: Aß-amyloid, tau and neurodegeneration AT(N), to generate a biomarker based definition of Alzheimer’s disease.ObjectivesTo stratify AIBL participants using the new NIA-AA Research Framework using cerebrospinal fluid (CSF) biomarkers. To evaluate the clinical and cognitive profiles of the different groups resultant from the AT(N) stratification. To compare the findings to those that result from stratification using two-biomarker construct criteria (AT and/or A(N)).DesignIndividuals were classified as being positive or negative for each of the A, T, and (N) categories and then assigned to the appropriate AT(N) combinatorial group: A−T−(N)−; A+T-(N)−; A+T+(N)−; A+T−(N)+; A+T+(N)+; A−T+(N)−; A−T−(N)+; A−T+(N)+. In line with the NIA-AA research framework, these eight AT(N) groups were then collapsed into four main groups of interest (normal AD biomarkers, AD pathologic change, AD and non-AD pathologic change) and the respective clinical and cognitive trajectories over 4.5 years for each group were assessed. In two sensitivity analyses the methods were replicated after assigning individuals to four groups based on being positive or negative for AT biomarkers as well as A(N) biomarkers.SettingTwo study centers in Melbourne (Victoria) and Perth (Western Australia), Australia recruited MCI individuals and individuals with AD from primary care physicians or tertiary memory disorder clinics. Cognitively healthy, elderly NCs were recruited through advertisement or via spouses of participants in the study.ParticipantsOne-hundred and forty NC, 33 MCI participants, and 27 participants with AD from the AIBL study who had undergone CSF evaluation using Elecsys® assays.Intervention (if any)Not applicable.MeasurementsThree CSF biomarkers, namely amyloid β1–42, phosphorylated tau181, and total tau, were measured to provide the AT(N) classifications. Clinical and cognitive trajectories were evaluated using the AIBL Preclinical Alzheimer Cognitive Composite (AIBL-PACC), a verbal episodic memory composite, an executive function composite, California Verbal Learning Test–Second Edition; Long-Delay Free Recall, Mini-Mental State Examination, and Clinical Dementia Rating Sum of Boxes scores.ResultsThirty-eight percent of the elderly NCs had no evidence of abnormal AD biomarkers, whereas 33% had biomarker levels consistent with AD or AD pathologic change, and 29% had evidence of non-AD biomarker change. Among NC participants, those with biomarker evidence of AD pathology tended to perform worse on cognitive outcome assessments than other biomarker groups. Approximately three in four participants with MCI or AD had biomarker levels consistent with the research framework’s definition of AD or AD pathologic change. For MCI participants, a decrease in AIBL-PACC scores was observed with increasing abnormal biomarkers; and increased abnormal biomarkers were also associated with increased rates of decline across some cognitive measures.ConclusionsIncreasing biomarker abnormality appears to be associated with worse cognitive trajectories. The implementation of biomarker classifications could help better characterize prognosis in clinical practice and identify those at-risk individuals more likely to clinically progress, for their inclusion in future therapeutic trials.
期刊介绍:
The JPAD « Journal of Prevention of Alzheimer’Disease » will publish reviews, original research articles and short reports to improve our knowledge in the field of Alzheimer prevention including : neurosciences, biomarkers, imaging, epidemiology, public health, physical cognitive exercise, nutrition, risk and protective factors, drug development, trials design, and heath economic outcomes.
JPAD will publish also the meeting abstracts from Clinical Trial on Alzheimer Disease (CTAD) and will be distributed both in paper and online version worldwide.